Instructions to use nblinh/91399fe4-b222-4443-a50e-66418956ddc5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh/91399fe4-b222-4443-a50e-66418956ddc5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "nblinh/91399fe4-b222-4443-a50e-66418956ddc5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35bc519786b22a0bc073fe7108636962d21d3782b72fe79fda19f157febaa5e0
- Size of remote file:
- 162 MB
- SHA256:
- 09dd0821061bc5ad887f4445eba0244c0252953471952430affd4ce31fe12edf
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